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相关概念视频

Sampling Distribution01:12

Sampling Distribution

13.6K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
13.6K
Sampling Methods: Overview01:06

Sampling Methods: Overview

538
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
538
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

454
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
454
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

362
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
362
Random Sampling Method01:09

Random Sampling Method

12.5K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
12.5K
Cluster Sampling Method01:20

Cluster Sampling Method

12.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.9K

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相关实验视频

Updated: Sep 19, 2025

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
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Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

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在生成性扩散模型中采用条件采样.

Zheng Zhao1,2, Ziwei Luo1, Jens Sjölund1

  • 1Department of Information Technology, Uppsala University, Uppsala, Sweden.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
|June 19, 2025
PubMed
概括
此摘要是机器生成的。

生成性扩散模型现在可以对复杂问题 (如贝叶斯反向问题) 取样条件分布. 本审查涵盖了使用联合或边际分布的方法,以改进条件生成抽样.

关键词:
贝叶斯的推理 贝叶斯的推理有条件的抽样.生成性扩散是一种产生性扩散.随机微分方程 随机微分方程

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

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相关实验视频

Last Updated: Sep 19, 2025

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
10:20

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

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科学领域:

  • 机器学习 机器学习
  • 计算统计学 计算统计学
  • 贝叶斯的推理是贝叶斯的推理.

背景情况:

  • 生成性扩散模型是用于高维分布的强大的蒙特卡洛采样器.
  • 目前在将这些模型应用于条件采样任务方面存在局限性,这对于贝叶斯反向问题至关重要.

研究的目的:

  • 为生成扩散模型中的条件采样提供计算方法的全面审查.
  • 突出构建条件生成样本的方法.

主要方法:

  • 审查利用联合分配进行条件抽样的技术.
  • 检查使用预训练的边际分布与明确的概率的检查方法.
  • 专注于生成性扩散模型中的计算方法.

主要成果:

  • 在生成性扩散模型中确定了条件采样的关键方法.
  • 基于使用联合或边际分布的分类方法.
  • 强调了某些边际分布方法中明确的概率的重要性.

结论:

  • 生成性扩散模型中的条件采样是一个活跃的研究领域,有各种计算策略.
  • 审查的方法提供了应用扩散模型到条件任务的途径,包括贝叶斯反向问题.
  • 这一领域的进一步发展有望为复杂的科学挑战提供生成建模的进步.